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Proceedings of the 19th Conference on Computer Science and Intelligence Systems (FedCSIS)

Annals of Computer Science and Information Systems, Volume 39

Pathomorphological Diagnosis Process Modeling for Machine Learning Algorithms’ Applying

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DOI: http://dx.doi.org/10.15439/2024F8289

Citation: Proceedings of the 19th Conference on Computer Science and Intelligence Systems (FedCSIS), M. Bolanowski, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 39, pages 237–242 ()

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Abstract. Business process management is oriented towards improving processes to best support people, who are working in them. Recent innovations in the area of artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), and distributed systems have provided opportunities for new technologies applications, including process automation. This paper aims at the pathomorphological diagnosis (PD) process modeling for the ML solution implementation. The research methods cover literature review and PD laboratory case study. Authors proposed the case study approach, because they argue that the PD process requires detailed analysis for its digitalization, automation, and combining with ML applications. Authors presented PD process models in BPMN notation, including laboratory equipment and emphasizing data and ML algorithms which are to be utilized in PD process digitalization for appropriate diagnosis for patients. Authors have found and emphasized that implementation of ML/AI algorithms is strongly based on fundamental process modeling

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